| gump vs King | 33–23 | 58.93% |
| gump vs Jin | 24–27 | 47.06% |
| gump vs Reina | 28–17 | 62.22% |
| gump vs Bryan | 16–21 | 43.24% |
| gump vs Kazuya | 20–15 | 57.14% |
| gump vs Dragunov | 18–12 | 60.00% |
| gump vs Lee | 18–11 | 62.07% |
| gump vs Lili | 11–16 | 40.74% |
| gump vs Paul | 8–18 | 30.77% |
| gump vs Yoshimitsu | 17–8 | 68.00% |
| gump vs Hwoarang | 9–16 | 36.00% |
| gump vs Eddy | 14–11 | 56.00% |
| gump vs Steve | 12–10 | 54.55% |
| gump vs Victor | 13–8 | 61.90% |
| gump vs Jun | 11–8 | 57.89% |
| gump vs Devil Jin | 13–5 | 72.22% |
| gump vs Lars | 10–8 | 55.56% |
| gump vs Jack-8 | 7–10 | 41.18% |
| gump vs Feng | 9–8 | 52.94% |
| gump vs Nina | 11–6 | 64.71% |
| gump vs Law | 9–7 | 56.25% |
| gump vs Armor King | 15–1 | 93.75% |
| gump vs Xiaoyu | 8–6 | 57.14% |
| gump vs Asuka | 9–4 | 69.23% |
| gump vs Azucena | 5–8 | 38.46% |
| gump vs Heihachi | 9–2 | 81.82% |
| gump vs Leo | 5–4 | 55.56% |
| gump vs Leroy | 4–3 | 57.14% |
| gump vs Clive | 5–2 | 71.43% |
| gump vs Claudio | 2–3 | 40.00% |
| gump vs Shaheen | 4–1 | 80.00% |
| gump vs Lidia | 3–1 | 75.00% |
| gump vs Alisa | 3–0 | 100.00% |
| gump vs Kuma | 3–0 | 100.00% |
| gump vs Raven | 1–2 | 33.33% |
| gump vs Anna | 1–2 | 33.33% |
| gump vs Panda | 1–1 | 50.00% |
| gump vs Zafina | 0–1 | 0.00% |
Limitations
This data is often requested to give insight into which characters you have more trouble with than others, but it is not particularly helpful for that. The main issue is that it is heavily skewed by how strong the opponents you play are.
For example, this data suggests my worst matchup is clearly vs Reina, but that's just because most of those games are vs Yagami.
There is a way to account for this being worked on. The central idea is to assign each matchup a rating vs you which adjusts based on the result, much like the regular rating but also based on the rating of each player. With this, it would give a better summary of how well you perform vs each character.
In the meantime, this page is here to present the data as requested.